| personal robbery | business robbery |
|---|---|
robbery, ATM location |
robbery, chain store |
Matt Ashby, Michèle Grace Bal, Gonzalo Croci, Ashly Fuller, Nicole Mantl and Lee Youngsub
📚 not updated since 2010
❌ no city-level data
💰 would be expensive to re-run
❓ only covers violent crime
🔒 rarely publicly available
🗄️ not designed for measuring crime
👉 use police-recorded crime data/statistics
🇪🇸 “robos con violencia en establecimientos” = “business robbery”
🇪🇸 “robos con fuerza en viviendas” = “residential burglary”
👉 translation by someone who understands crime data
A person smashes the window on a parked car and removes money from the glove box, intending to spend the money on drugs and without the permission of the vehicle owner.
🌏 theft from a motor vehicle
🏄 auto burglary
👉 produce harmonised categories from published data
| personal robbery | business robbery |
|---|---|
robbery, ATM location |
robbery, chain store |
‘Small’ London
London – 5km buffer
1,024 robberies
per 100,000 residents
London
858 robberies
per 100,000 residents
‘Big’ London
London + 5km buffer
785 robberies
per 100,000 residents
👉 create comparable ‘cities’ from existing areas with published crime data
👉 compare trends rather than point estimates
… translated appropriately
… aggregated to harmonised categories
… for equivalent geographic areas
Slides:
https://lesscrime.info/talk/ecca-2024/
Questions:
matthew.ashby@ucl.ac.uk
Funding thanks:
Metropolitan Police Service